About MapReduce MapReduce is a programming model specifically implemented for processing large data sets. The model was developed by Jeffrey Dean and Sanjay Ghemawat at Google (see “ MapReduce ...

MapReduce is also important because many graduates are emerging from universities with MapReduce programming experience.

Hadoop Streaming allows developers to use virtually any programming language to create MapReduce jobs, but it’s a bit of a kludge. The MapReduce programming environment needs to be pluggable.

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

A recent article on the Database Column by David J. DeWitt and Michael Stonebraker attempts to compare the increasingly popular MapReduce programming paradigm to a relational database. The ...

Hadoop MapReduce has been widely embraced for analyzing large, static data sets. New technology integrates a stand-alone MapReduce engine into an in-memory data grid, enabling real-time analytics on ...

Two Google Fellows just published a paper in the latest issue of Communications of the ACM about MapReduce, the parallel programming model used to process more than 20 petabytes of data every day ...

MapReduce programming will still be required, of course, but SQL support makes the results rapidly accessible to many more people.

The market for software related to the Hadoop and MapReduce programming frameworks for large-scale data analysis will jump from US$77 million in 2011 to $812.8 million in 2016, a compound annual ...

Hadoop is the most significant concrete technology behind the so called 'Big Data' revolution. Hadoop combines an economical model for storing massive quantities of data - the Hadoop Distributed File ...